Responsibilities:

• Construct a high-level overview of the entire data landscape of the organization.
  
• Illustrate how data moves through the organization and between systems.
  
• Develop high-level designs outlining the main entities and their relationships.
  
• Design detailed models showing attributes, primary keys, and relationships between entities without considering physical aspects.
  
• Implement designs showing how data will be stored, including tables, columns, indexes, and relationships.
  
• Design diagrams showing how different data systems and databases interact and are integrated.
  
• Document standards and policies for data management, including naming conventions, data quality standards, and data security policies.
  
• Plan and guide the roles and responsibilities of data stewards in maintaining data quality and integrity.
  
• Compile detailed descriptions of data elements, their meanings, and their relationships.
  
• Create a comprehensive list of business terms and their definitions to ensure consistent usage across the organization.
  
• Document and design processes for extracting, transforming, and loading data from various sources.
  
• Strategize and schedule the movement of data from legacy systems to new systems or platforms.
  
• Detail the design of the data warehouse, including the schema, dimensions, and fact tables.
  
• Set up and configure BI tools and dashboards.
  
• Regularly report on the quality of data, identifying issues and areas for improvement.
  
• Develop strategies and methods for cleaning and improving the quality of data.
  
• Plan and diagram how data security will be implemented and maintained.
  
• Document compliance with relevant regulations and standards.
  
• Develop strategies for improving the efficiency and performance of data systems.
  
• Detail plans for data architecture projects, including timelines, milestones, and resources required.
  
• Document technical specifications for all data architecture components and processes.
  

MUST HAVES:

7+years experiences in the following:

• developing conceptual, logical and physical data models for structured, semi-structured, and unstructured data with relational, star and snowflake schemas.
  
• Proficiency in data modeling methods and tools (e.g. ERWIN, VISIO, Power Designer).
  
• developing and implementing common data models and master data management strategies
  
• design schemas that balance agility, schema flexibility, data governance, and quality.
  
• Expertise in creating schemas that allow flexible querying and analysis across various data formats.
  
• defining data partitioning, clustering, and indexing strategies to optimize query performance and data access patterns.
  
• implementing schemas and metadata structures that support efficient data management.
  
• Understanding of data governance principles and practices, especially in designing schemas and metadata structures.
  
• Experience in creating Architecture Artefacts based on enterprise standards.
  
• 4+ years experience in designing schemas that integrate diverse data types stored in a data lake or data lakehouse.
  
• 3+ years experience of implementing Medallion architecture or similar frameworks. Familiarity with tools and techniques for managing metadata in a data lakehouse environment.
  
• Hands-on experience with Azure services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks
  
• 10+ years experience with Solutions development.
  
• Experience in addressing complex data integration challenges and design efficient, scalable data models.
  
• Experience in monitoring and enforcing data modelling/normalization standards.